baseline-estimate

This repo is for baseline correction. Both parameter estimation and non-parameter estimation of the baseline are available.

Prerequisites

• Python 3
• numpy, scipy, math (only required for non-parameter estimation's SNIP methods), nlopt (only required for parameter estimation)

Usage

Class NONPARAMS_EST in nonparams_est.py provides two series of methods.

• snip: Sensitive Nonlinear Iterative Peak (SNIP) algorithms.
• pls: Reweighted Penalized Least Squares (PLS) algorithms. the AsLS, airPLS, arPLS, BrPLS methods are available.

Class PARAMES_EST in params_est.py provides parameter baseline method based on Bayesian theorem.

• ESTFUNC: function of the baseline to be estimated. default: linear, quadratic, cubic, Lorentzian, Landau-Gaussian (pylandau required). Also user can define custom functions.
• BAYESIAN: main function for baseline estimation.

Example

Examples of all the methods to estimate Gaussian peaks on linear and Lorentzian baseline are shown in test.py.

License

This repository is licensed under the GNU GPLv3.

Cite

Q. Wang, X.L Yan, et al. NUCL SCI TECH, 33: 148 (2022). doi: 10.1007/s41365-022-01132-9